This article is a collection of tutorials on TensorFlow's implementation of popular machine learning algorithms. The goal is to make it easy for readers to get a deeper understanding of TensorFlow through clear and concise cases. These cases are suitable for beginners who want to implement some TensorFlow cases. This tutorial also contains notes and annotated code. The first step: a tutorial guide for TF novices 1:tf beginners need to understand the preparation for getting started Machine learning entry notes: 2: tf beginners need to understand the basics of getting started Hello World Basic operation 3: basic model that tf beginners need to master Nearest neighbor: Linear regression: LogisTIc regression: 4: tf beginners need to try the neural network Multilayer perceptron: Convolutional neural network: Recurrent Neural Network (LSTM): Two-way Cyclic Neural Network (LSTM): Dynamic Recurrent Neural Network (LSTM) Self-encoder 5: tf beginners need proficient practical technology Save and restore models Graph and loss visualization Tensorboard - advanced visualization 5: tf beginners need to understand the basic operation of multiple GPUs Basic operations on multiple GPUs 6: The data set needed for the case There are some cases where MNIST data sets are required for training and testing. When you run these cases, the dataset is automatically downloaded (using input_data.py). Step 2: Various types of cases, models, and data sets for TF novices Initial understanding: TFLearn TensorFlow Basic model and data set Linear regression, linear regression using TFLearn Computer vision model and data set
Immersion Cooling is a technique used to cool components of IT equipment that consists of submerging the computer components in a thermally conductive and dielectric liquid. Through this practice, the servers are cooled and heat is transferred from the source to the liquid.
water cooling,oil cooling,immersion cooling box,liquid immersion cooling,apw12 power supply Shenzhen YLHM Technology Co., Ltd. , https://www.hkcryptominer.com
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/noteboo...
MNIST dataset entry notes
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/noteboo...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/noteboo...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/example...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/noteboo...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/example...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/noteboo...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/example...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/noteboo...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/example...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/noteboo...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/example... 
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/noteboo...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/example...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/noteboo...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/example...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/noteboo...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/example...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/noteboo...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/example...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/example...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/noteboo...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/example...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/noteboo...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/example...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/noteboo...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/example...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/example...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/noteboo...
Https://github.com/aymericdamien/TensorFlow-Examples/blob/master/example...
MNIST dataset notes: https://github.com/aymericdamien/TensorFlow-Examples/blob/master/noteboo...
Official website:
The next example comes from TFLearn, a library that provides a simplified interface to TensorFlow. There are many examples and pre-built operations and layers.
Use the tutorial: TFLearn Quick Start. Learn the TFLearn foundation through a specific machine learning task. Develop and train a deep neural network classifier.
TFLearn address: https://github.com/tflearn/tflearn
Example: https://github.com/tflearn/tflearn/tree/master/examples
Pre-built operations and layers: #api
Notes: https://github.com/tflearn/tflearn/blob/master/tutorials/intro/quickstart.md
Https://github.com/tflearn/tflearn/blob/master/examples/basics/linear_re...
Logical Operators. Implement logical operators with TFLearn
Https://github.com/tflearn/tflearn/blob/master/examples/basics/logical.py
The weight is maintained. Save and restore a model
Https://github.com/tflearn/tflearn/blob/master/examples/basics/weights_p...
Fine tune. Fine-tuning a pre-trained model on a new task
Https://github.com/tflearn/tflearn/blob/master/examples/basics/finetunin...
Use HDF5. Handling large data sets with HDF5
Https://github.com/tflearn/tflearn/blob/master/examples/basics/use_hdf5.py
Use DASK. Working with large data sets using DASK
Https://github.com/tflearn/tflearn/blob/master/examples/basics/use_dask.py
When we talk about Immersion Cooling, we also need to discuss the different types of Immersion Cooling, as well as the applications of Immersion cooling. The practice of Immersion Cooling has a multitude of benefits particularly as it allows datacenters to be managed in a greener and more sustainable manner. Environmental concerns has been a huge catalyst for the adoption of the technology in recent years.
deionized water
mineral oil
fluorocarbon-based fluids
synthetic
Immersion Cooling systems used to have a higher fluid cost than water cooling, but this is already changing.
A wide variety of liquids exist for this purpose, the most suitable being transformer oils and other electrical cooling oils. Non-purpose oils, including cooking, motor and silicone oils, have been successfully used for cooling personal computers